A Positive Resampler for Monte Carlo events with negative weights
(2020) In European Physical Journal C 80(11).- Abstract
We propose the Positive Resampler to solve the problem associated with event samples from state-of-the-art predictions for scattering processes at hadron colliders typically involving a sizeable number of events contributing with negative weight. The proposed method guarantees positive weights for all physical distributions, and a correct description of all observables. A desirable side product of the method is the possibility to reduce the size of event samples produced by General Purpose Event Generators, thus lowering the resource demands for subsequent computing-intensive event processing steps. We demonstrate the viability and efficiency of our approach by considering its application to a next-to-leading order + parton shower... (More)
We propose the Positive Resampler to solve the problem associated with event samples from state-of-the-art predictions for scattering processes at hadron colliders typically involving a sizeable number of events contributing with negative weight. The proposed method guarantees positive weights for all physical distributions, and a correct description of all observables. A desirable side product of the method is the possibility to reduce the size of event samples produced by General Purpose Event Generators, thus lowering the resource demands for subsequent computing-intensive event processing steps. We demonstrate the viability and efficiency of our approach by considering its application to a next-to-leading order + parton shower merged prediction for the production of a W boson in association with multiple jets.
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- author
- Andersen, Jeppe R. ; Gütschow, Christian ; Maier, Andreas and Prestel, Stefan LU
- organization
- publishing date
- 2020
- type
- Contribution to journal
- publication status
- published
- subject
- in
- European Physical Journal C
- volume
- 80
- issue
- 11
- article number
- 1007
- publisher
- Springer
- external identifiers
-
- scopus:85094965336
- ISSN
- 1434-6044
- DOI
- 10.1140/epjc/s10052-020-08548-w
- language
- English
- LU publication?
- yes
- id
- ad979b9a-5c3d-4f7f-bfde-9a94af2c8a41
- date added to LUP
- 2020-11-16 07:46:01
- date last changed
- 2024-04-17 18:44:47
@article{ad979b9a-5c3d-4f7f-bfde-9a94af2c8a41,
abstract = {{<p>We propose the Positive Resampler to solve the problem associated with event samples from state-of-the-art predictions for scattering processes at hadron colliders typically involving a sizeable number of events contributing with negative weight. The proposed method guarantees positive weights for all physical distributions, and a correct description of all observables. A desirable side product of the method is the possibility to reduce the size of event samples produced by General Purpose Event Generators, thus lowering the resource demands for subsequent computing-intensive event processing steps. We demonstrate the viability and efficiency of our approach by considering its application to a next-to-leading order + parton shower merged prediction for the production of a W boson in association with multiple jets.</p>}},
author = {{Andersen, Jeppe R. and Gütschow, Christian and Maier, Andreas and Prestel, Stefan}},
issn = {{1434-6044}},
language = {{eng}},
number = {{11}},
publisher = {{Springer}},
series = {{European Physical Journal C}},
title = {{A Positive Resampler for Monte Carlo events with negative weights}},
url = {{http://dx.doi.org/10.1140/epjc/s10052-020-08548-w}},
doi = {{10.1140/epjc/s10052-020-08548-w}},
volume = {{80}},
year = {{2020}},
}